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Contractual Full Stack Data Scientist Jobs (NOW HIRING)

AIToolboard

Full Stack Data Scientist (AI/ML)

Reston, VA · On-site

$120 - $160/hr

# Full Stack Data Scientist (AI/ML)Technology VenturesReston, USContractor## About the RoleReston, VAContractJun 2, 2026Full Stack Data Scientist (AI/ML) -We are seeking a Full Stack Data Scientist to ...

rockITdata

Full Stack Data Scientist

Arlington, VA · Remote

We are seeking a highly skilled and innovative Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering ...

rockITdata

Full Stack Data Scientist

Arlington, VA · On-site +1

We are seeking a highly skilled and innovative Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering ...

CREW

Full-Stack Data Scientist

Manhattan, NY · On-site

$90 - $120/hr

About the Role We are looking for a product-focused data scientist and developer to join CREW's Platform Team. This person designs and implements data products to enable other CREW teams and to ...

CREW Carbon, Inc.

Full-Stack Data Scientist

Manhattan, NY · On-site

$90 - $120/hr

About the Role We are looking for a product-focused data scientist and developer to join CREW's Platform Team. This person designs and implements data products to enable other CREW teams and to ...

RPMGlobal

Full-Stack Data Engineer

Miami, FL · On-site

$120 - $160/hr

Bachelor's degree in Computer Science, Data Engineering, or a related field OR a minimum of 5 years of equivalent experience in full-stack development and data engineering. * Demonstrated experience ...

Prescient Edge

Full-Stack Data Engineer

Doral, FL · On-site

Bachelor's degree in computer science, Data Engineering, Geospatial Information Systems (GIS), or a related field, or five (5) years of equivalent experience in data engineering, full-stack ...

Hearst

Full-Stack Data Engineer

Troy, MI

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

Hearst

Full-Stack Data Engineer

Troy, MI · On-site

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

Prescient Edge

NY · On-site

$90 - $120/hr

Bachelor's degree in computer science, Data Engineering, Geospatial Information Systems (GIS), or a related field, or five (5) years of equivalent experience in data engineering, full-stack ...

Hearst Newspapers

Full-Stack Data Engineer

Troy, MI · On-site

FULL-STACK DATA ENGINEER at MOTOR INFORMATION SYSTEMS MOTOR Information Systems, an operating group of Hearst, is actively seeking a Full-Stack Data Engineer. Ideally, a hands-on data engineer who ...

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Contractual Full Stack Data Scientist information

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$46K

$165K

$243.5K

How much do contractual full stack data scientist jobs pay per year?

As of Aug 28, 2026, the average yearly pay for contractual full stack data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a contractual full stack data scientist?

Contractual Full Stack Data Scientists are professionals hired on a contract basis to manage the end-to-end data science workflow for an organization. They are skilled in both frontend and backend development, as well as data engineering, data analysis, and machine learning. Their responsibilities often include collecting, processing, and analyzing data, developing predictive models, and deploying solutions into production environments. Unlike permanent employees, they typically work on specific projects or for a set period, offering flexibility to both the employer and the professional.

What are the key skills and qualifications needed to thrive as a contractual full stack data scientist?

To thrive as a Contractual Full Stack Data Scientist, you need strong expertise in statistics, machine learning, data analysis, and software engineering, typically supported by a relevant degree and a portfolio of completed projects. Familiarity with programming languages such as Python or R, cloud platforms like AWS or Azure, and tools such as TensorFlow, SQL, and version control systems is essential. Excellent problem-solving, communication, and time management skills help you adapt quickly to varied client needs and collaborate effectively with cross-functional teams. These skills ensure the ability to deliver end-to-end data solutions that drive business value within project deadlines.

What are some common challenges faced by contractual full stack data scientists, and how can they be addressed?

Contractual full stack data scientists often face challenges such as adapting quickly to new teams and business domains, managing time constraints, and ensuring seamless handover of work at project completion. Since these roles typically involve both backend and frontend tasks, balancing diverse technical responsibilities while aligning with client expectations can be demanding. To address these challenges, it’s helpful to establish clear communication channels, document work thoroughly, and set realistic deliverables early in the contract. Proactively engaging with stakeholders and being flexible with new tools or workflows also support successful project outcomes.

What is the difference between Contractual Full Stack Data Scientist vs Contractual Data Engineer?

AspectContractual Full Stack Data ScientistContractual Data Engineer
CredentialsDegree in Data Science, Computer Science, or related field; certifications in data analysis or machine learningDegree in Computer Engineering, Software Engineering, or related; certifications in cloud platforms or data pipeline tools
Work EnvironmentCollaborates with data analysts, machine learning engineers, and business teams on modeling and insightsFocuses on building, maintaining, and optimizing data pipelines and infrastructure
Industry UsageUsed across industries for data analysis, predictive modeling, and business insightsPrimarily in tech, finance, and e-commerce for data infrastructure and ETL processes

The Contractual Full Stack Data Scientist combines data analysis, modeling, and software skills to deliver insights and solutions, while the Contractual Data Engineer specializes in building and maintaining data infrastructure. Both roles are essential in data-driven organizations but focus on different aspects of the data lifecycle.

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Contractual Full Stack Data Scientist jobs near you
Infographic showing various Contractual Full Stack Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Full Stack Data Scientist (AI/ML)

AIToolboard

Reston, VA • On-site

$120 - $160/hr

Other

Posted 22 days ago

Job description

# Full Stack Data Scientist (AI/ML)Technology VenturesReston, USContractor## About the RoleReston, VAContractJun 2, 2026Full Stack Data Scientist (AI/ML) -We are seeking a Full Stack Data Scientist to develop AI/ML solutions end-to-end, from business problem formulation and model development through production-ready application delivery and operationalization. This role combines deep modeling expertise, strong software engineering skills, and practical MLOps experience. The ideal candidate builds models that matter, writes code that lasts, and partners with platform teams to deploy, monitor, and operate AI/ML solutions efficiently and reliably at scale.Key Responsibilities• Translate complex business requirements into AI/ML-based technical solutions and ensure efficiency, scalability and reliability• Design, develop, validate, and document AI/ML models and applications• Build production-grade Python code and pipelines for data processing, feature engineering, training, and inference.• Develop model-driven applications and services (batch or real-time).• Apply software engineering best practices including modular design, testing, code reviews, and CI/CD.• Collaborate with MLOps teams on deployment, monitoring, versioning, and retraining.• Implement model performance, stability, and data drift monitoring.• Produce documentation to support governance, validation, and audit requirements.Required Qualifications• Proven hands-on experience (6+ years preferred) in production-ready models and applications that solve real business problems while actively participating in MLOps to ensure solutions operate reliably in production.• Strong experience in statistical modeling, machine learning, AI, and applied analytics.• Advanced proficiency in Python, ML libraries, SQL, and big data processing (e.g. pandas, NumPy, scikit-learn, TensorFlow, PySpark ).• Experience writing production-ready, maintainable code and application design.• Strong experience with AWS cloud ML platforms (e.g., AWS SageMaker, MLFlow, S3, compute services, Redshift).• Experience with model deployment and MLOps practices• Strong problem-solving and communication skills.EducationBachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field. #J-18808-Ljbffr

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